Python expert for Analyze and existing dataset and extract extra features from an existing one
Budget: $10 – $50 USD
first column K in the excel sheet (description ) has several alarms and events, we need to explore the relationship between those alarms /events and find the statistical relations between that events, and identify if there is any coloration between those events /alarms that are considering a specific Sid ( which represents a single device in a single location ),s detailed Exploratory data analysis required.
the second request for column G, this column contains raw msgs from the different protocols ( the msg format explained below ) the raw column contains lots of information, Account like identifying format to receiver, Event code, Zone Number, etc ) our concern is to :
a) extract the Zone number from the raw column ( G)
b) combined the zone number with the respective Sid number ( column B ) for each row in the data set,
c) the combination of the zone and sid will create a new column which will have a new unique ID ( zone + SID)
d) the new column can be used to compare the timing between the event/alarm that happened at each raw and the restoral event that happened after word maybe next raw or next few raws, we will use the ( zone + sid ) to distinguish each alarm and restoral.
e) calculate the delta between the event and restoral using column (H) uatime column,
f) we need to build logic around delta by which if delta is lower than 5 minutes, the event and restoral will be tagged as a false event ( creating a new column as a target column ) if delta is more than 5 minutes the alarm and event will be considered as true,
Analyze an existing dataset and extract extra features from an existing steam ( specific format ), basically to extract a known field using Regex or any other suitable method, also compare the extracted features ( event and response ) occurrence timing to create a new column for the dataset as a label, this label column will be the target in the training dataset in the later stage.
thank you.
the second request for column G, this column contains raw msgs from the different protocols ( the msg format explained below ) the raw column contains lots of information, Account like identifying format to receiver, Event code, Zone Number, etc ) our concern is to :
a) extract the Zone number from the raw column ( G)
b) combined the zone number with the respective Sid number ( column B ) for each row in the data set,
c) the combination of the zone and sid will create a new column which will have a new unique ID ( zone + SID)
d) the new column can be used to compare the timing between the event/alarm that happened at each raw and the restoral event that happened after word maybe next raw or next few raws, we will use the ( zone + sid ) to distinguish each alarm and restoral.
e) calculate the delta between the event and restoral using column (H) uatime column,
f) we need to build logic around delta by which if delta is lower than 5 minutes, the event and restoral will be tagged as a false event ( creating a new column as a target column ) if delta is more than 5 minutes the alarm and event will be considered as true,
Analyze an existing dataset and extract extra features from an existing steam ( specific format ), basically to extract a known field using Regex or any other suitable method, also compare the extracted features ( event and response ) occurrence timing to create a new column for the dataset as a label, this label column will be the target in the training dataset in the later stage.
thank you.